Skip to main content

EQPO: Obscuring Encrypted Web Traffic with Equal-Sized Pseudo-Objects

Part of the Lecture Notes in Computer Science book series (LNSC,volume 9589)

Abstract

Internet users are concerned with their private web browsing behaviors. Browsing a webpage introduces a typical request-response-based network traffic which is associated with the structure of corresponding HTML document. This may make the traffic of a specified webpage demonstrate different features from others even when the traffic is encrypted. Traffic analysis techniques can be used to extract those features to identify that webpage, and hence the webpages the user visited could be disclosed though they might be encrypted. In this paper, we propose EQPO, a method to defend against traffic analysis by obscuring web traffic with EQual-sized Pseudo-Objects. A pseudo-object is composed by some original objects, object fragments, or padding octets. We define a structure of EQPO-enabled HTML document to force object requests and responses be on pseudo-objects. For a webpage set, by equalizing the sizes of pseudo-objects and the numbers of pseudo-objects requests in each webpage, we can make the traffic for those webpages with no identifiable features. We have implemented a proof of concept prototype and validate the proposed countermeasure with some state of the art traffic analysis techniques.

Keywords

  • Encrypted web traffic
  • Webpage identification
  • Traffic analysis
  • Equal-sized pseudo-object

This is a preview of subscription content, access via your institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • DOI: 10.1007/978-3-319-38898-4_14
  • Chapter length: 19 pages
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
eBook
USD   64.99
Price excludes VAT (USA)
  • ISBN: 978-3-319-38898-4
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Softcover Book
USD   84.99
Price excludes VAT (USA)
Fig. 1.
Fig. 2.
Fig. 3.
Fig. 4.
Fig. 5.
Fig. 6.

References

  1. Bissias, G.D., Liberatore, M., Jensen, D., Levine, B.N.: Privacy vulnerabilities in encrypted HTTP streams. In: Danezis, G., Martin, D. (eds.) PET 2005. LNCS, vol. 3856, pp. 1–11. Springer, Heidelberg (2006)

    CrossRef  Google Scholar 

  2. Chen, S., Wang, R., Wang, X., Zhang, K.: Side-channel leaks in web applications: a reality today, a challenge tomorrow. In: Proceedings of IEEE S&P 2010, pp. 191–206 (2010)

    Google Scholar 

  3. Dyer, K., Coull, S., Ristenpart, T., Shrimpton, T.: Peek-a-Boo, I still see you: why traffic analysis countermeasures fail. In: Proceedings of IEEE S&P 2012, pp. 332–346 (2012)

    Google Scholar 

  4. Herrmann, D., Wendolsky, R., Federrath, H.: Website fingerprinting: attacking popular privacy enhancing technologies with the multinomial Naïve-bayes classifier. In: Proceedings of CCSW 2009, pp. 31–42 (2009)

    Google Scholar 

  5. Liberatore, M., Levine, B.: Inferring the source of encrypted HTTP connections. In: Proceedings of ACM CCS 2006, pp. 255–263 (2006)

    Google Scholar 

  6. Lu, L., Chang, E.-C., Chan, M.C.: Website fingerprinting and identification using ordered feature sequences. In: Gritzalis, D., Preneel, B., Theoharidou, M. (eds.) ESORICS 2010. LNCS, vol. 6345, pp. 199–214. Springer, Heidelberg (2010)

    CrossRef  Google Scholar 

  7. Luo, X., Zhou, P., Chan, E., Lee, W., Chang, R.: HTTPOS: sealing information leaks with browserside obfuscation of encrypted flows. In: Proceedings of NDSS 2011 (2011)

    Google Scholar 

  8. Miller, B., Huang, L., Joseph, A.D., Tygar, J.D.: I know why you went to the clinic: risks and realization of HTTPS traffic analysis. In: De Cristofaro, E., Murdoch, S.J. (eds.) PETS 2014. LNCS, vol. 8555, pp. 143–163. Springer, Heidelberg (2014)

    Google Scholar 

  9. Panchenko, A., Niessen, L., Zinnen, A., Engel, T.: Website fingerprinting in onion routing based anonymization networks. In: Proceedings of ACM WPES 2011, pp. 103–114 (2011)

    Google Scholar 

  10. Sun, Q., Simon, D., Wang, Y., Russell, W., Padmanabhan, V., Qiu, L.: Statistical identification of encrypted web browsing traffic. In: Proceedings of IEEE S&P 2002, pp. 19–30 (2002)

    Google Scholar 

  11. Sweeney, L.: k-anonymity: a model for protecting privacy. Int. J. Uncertainty Fuzziness Knowl. Based Syst. 10(5), 557–570 (2002)

    MathSciNet  CrossRef  MATH  Google Scholar 

  12. Tang, Y., Lin, P., Luo, Z.: Obfuscating encrypted web traffic with combined objects. In: Huang, X., Zhou, J. (eds.) ISPEC 2014. LNCS, vol. 8434, pp. 90–104. Springer, Heidelberg (2014)

    CrossRef  Google Scholar 

  13. Tang, Y., Lin, P., Luo, Z.: psOBJ: Defending against traffic analysis with pseudo-objects. In: Au, M.H., Carminati, B., Kuo, C.-C.J. (eds.) NSS 2014. LNCS, vol. 8792, pp. 96–109. Springer, Heidelberg (2014)

    Google Scholar 

  14. Wang, T., Goldberg, I.: Improved website fingerprinting on tor. In: Proceedings of WPES 2013, pp. 201–212 (2013)

    Google Scholar 

  15. Wright, C., Coull, S., Monrose, F.: Traffic morphing: an efficient defense against statistical traffic analysis. In: Proceedings of NDSS 2009, pp. 237–250 (2009)

    Google Scholar 

  16. Masinter, L.: The “data” URL scheme. http://www.ietf.org/rfc/rfc2397.txt

  17. https://github.com/kpdyer/traffic-analysis-framework

  18. http://masaka.cs.ohiou.edu/eblanton/tcpurify/

Download references

Acknowledgments

This paper was partially supported by the National Natural Science Foundation of China under Grant 61472091.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Yi Tang .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and Permissions

Copyright information

© 2016 Springer International Publishing Switzerland

About this paper

Cite this paper

Tang, Y., Lin, M. (2016). EQPO: Obscuring Encrypted Web Traffic with Equal-Sized Pseudo-Objects. In: Lin, D., Wang, X., Yung, M. (eds) Information Security and Cryptology. Inscrypt 2015. Lecture Notes in Computer Science(), vol 9589. Springer, Cham. https://doi.org/10.1007/978-3-319-38898-4_14

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-38898-4_14

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-38897-7

  • Online ISBN: 978-3-319-38898-4

  • eBook Packages: Computer ScienceComputer Science (R0)